1 citations · 1 across the 1 of their papers we have counts for
6 papers
Improve Student's Reasoning Generalizability through Cascading Decomposed CoTs Distillation
Chengwei Dai, Kun Li, Wei Zhou +1
Large language models (LLMs) exhibit enhanced reasoning at larger scales, driving efforts to distill these capabilities into smaller models via teacher-student learning. Previous w…
Beyond Imitation: Learning Key Reasoning Steps from Dual Chain-of-Thoughts in Reasoning Distillation
Chengwei Dai, Kun Li, Wei Zhou +1
As Large Language Models (LLMs) scale up and gain powerful Chain-of-Thoughts (CoTs) reasoning abilities, practical resource constraints drive efforts to distill these capabilities…
Are Large Language Models Good Fact Checkers: A Preliminary Study
Han Cao, Lingwei Wei, Mengyang Chen +2
Recently, Large Language Models (LLMs) have drawn significant attention due to their outstanding reasoning capabilities and extensive knowledge repository, positioning them as supe…
CT-GAT: Cross-Task Generative Adversarial Attack based on Transferability
Minxuan Lv, Chengwei Dai, Kun Li +2
Neural network models are vulnerable to adversarial examples, and adversarial transferability further increases the risk of adversarial attacks. Current methods based on transferab…
Explore the Potential of LLMs in Misinformation Detection: An Empirical Study
Mengyang Chen, Lingwei Wei, Han Cao +2
Large Language Models (LLMs) have garnered significant attention for their powerful ability in natural language understanding and reasoning. In this paper, we present a comprehensi…
HC3 Plus: A Semantic-Invariant Human ChatGPT Comparison Corpus
Zhenpeng Su, Xing Wu, Wei Zhou +2
ChatGPT has garnered significant interest due to its impressive performance; however, there is growing concern about its potential risks, particularly in the detection of AI-genera…